"""Domain value objects for Autonomous Agentic AML Copilot & RAG Narrative Generator."""

from __future__ import annotations

from dataclasses import dataclass
from typing import Any

from app.application.schemas.copilot import (
    AssembledEvidenceResponse,
    CopilotDirectGenerationRequest,
    CopilotQueryRequest,
    CopilotQueryResponse,
    CopilotStatusResponse,
)


@dataclass(frozen=True)
class AMLCopilotAnalysis:
    """Container holding synthesized BSA/AML copilot findings and regulatory narrative.

    Adheres to FinCEN Guidance FIN-2007-G003 5-paragraph SAR narrative structure.
    """

    case_id: str
    fincen_sar_narrative: str  # 5-paragraph FinCEN SAR narrative in Markdown format
    four_eyes_briefing: str  # Supervisor 4-eyes dual-signoff briefing summary
    recommended_action: str  # e.g., 'CONFIRMED_SAR', 'ESCALATE_TO_FIU', 'MONITOR_ACCOUNT'
    top_risk_drivers: list[dict[str, Any]]  # List of SHAP feature attributions
    graph_topology_summary: dict[str, Any]  # Louvain community, PageRank, layering hops
    zero_pii_verified: bool
    generated_at_timestamp: float
    lineage_hash: str  # SHA-256 block hash for audit lineage
    evidence_count: int = 0
    timeline_event_count: int = 0


@dataclass(frozen=True)
class CaseEvidenceDossier:
    """Assembled evidence package aggregated across timeline events, notes, and registered artifacts."""

    case_id: str
    case_title: str
    case_status: str
    total_risk_score: float
    alert_ids: list[str]
    timeline_events: list[dict[str, Any]]
    evidence_artifacts: list[dict[str, Any]]
    investigator_notes: list[str]
    shap_drivers: list[dict[str, Any]]
    graph_topology: dict[str, Any]
    pii_sanitized_count: int
    evidence_hash: str
    assembled_at: float


__all__ = [
    "AMLCopilotAnalysis",
    "CaseEvidenceDossier",
    "CopilotQueryRequest",
    "CopilotDirectGenerationRequest",
    "CopilotQueryResponse",
    "AssembledEvidenceResponse",
    "CopilotStatusResponse",
]